Category: Courses
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Best practices for robust feature pipelines
Building robust feature pipelines is essential for maintaining accuracy, scalability, and reliability in modern machine learning systems. This post explores engineering best practices, tools, and architectures that leading companies use to ensure feature pipelines remain maintainable, testable, and resilient from development to production.
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Tools: AWS Lake Formation, Glue Data Catalog
AWS Lake Formation and Glue Data Catalog are two powerful services that streamline data lake management, access control, and metadata organization. This post explores how these tools integrate to build secure, discoverable, and governed data ecosystems on AWSâcovering architecture, best practices, and real-world enterprise use cases.
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Introduction to async/await in Python
Asynchronous programming in Python allows developers to write highly efficient, non-blocking applications. This article introduces async and await, explains the event loop, and shows how to build concurrent I/O operations using standard libraries like asyncio. Perfect for developers new to async concepts or transitioning from synchronous codebases.
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Best practices for wheel and source distributions
This blog post explores best practices for wheel and source distributions in Python, focusing on strategies to ensure efficient packaging, distribution, and installation. It covers essential tools, CI/CD integration, private repositories, and code imports for various environments such as Jupyter notebooks and AWS Lambda.
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Empirical: comparing SOLID vs non-SOLID Python code maintainability
In this empirical exploration, we compare the maintainability of Python code that follows SOLID principles versus code that does not. By examining real-world examples, code complexity metrics, and developer effort over time, we uncover how applying SOLID affects code readability, changeability, and long-term stability.